import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
df = pd.read_csv('scores.csv')
df.head(18)
| Place | Car Num | Team | Penalty | Cost Score | Presentation Score | Design Score | Acceleration Score | Skid Pad Score | Autocross Score | Endurance Score | Efficiency Score | Total Score | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 44 | Univ of Illinois - Urbana Champaign | 0 | 87.4 | 40.1 | 150 | 76.4 | 48.2 | 121.0 | 275.0 | 56.1 | 854.2 |
| 1 | 2 | 119 | Villanova Univ | 0 | 67.3 | 58.4 | 115 | 94.8 | 53.1 | 111.1 | 238.1 | 100.0 | 837.8 |
| 2 | 3 | 67 | Univ of Florida | 0 | 58.7 | 49.2 | 135 | 100.0 | 40.7 | 123.4 | 229.7 | 58.8 | 795.5 |
| 3 | 4 | 54 | Kettering Univ | 0 | 66.2 | 49.1 | 100 | 85.6 | 45.4 | 121.7 | 205.0 | 70.6 | 743.6 |
| 4 | 5 | 96 | University of Alabama - Tuscaloosa | 0 | 65.1 | 64.1 | 100 | 85.2 | 59.2 | 111.7 | 184.9 | 61.9 | 732.1 |
| 5 | 6 | 52 | Purdue Univ - W. Lafayette | 0 | 72.6 | 74.8 | 135 | 59.9 | 66.2 | 109.5 | 146.0 | 64.4 | 728.4 |
| 6 | 7 | 68 | Louisiana State Univ | 0 | 65.2 | 53.6 | 80 | 77.6 | 70.8 | 117.7 | 184.9 | 57.0 | 706.7 |
| 7 | 8 | 115 | Univ of Akron | 0 | 69.7 | 47.7 | 115 | 51.5 | 30.9 | 94.9 | 211.8 | 64.1 | 685.7 |
| 8 | 9 | 48 | North Carolina State Univ - Raleigh | 0 | 74.5 | 60.5 | 105 | 73.3 | 57.1 | 57.4 | 190.8 | 60.1 | 678.6 |
| 9 | 10 | 104 | Univ of Connecticut | 0 | 80.3 | 32.2 | 100 | 0.0 | 40.3 | 123.2 | 233.3 | 48.3 | 657.5 |
| 10 | 11 | 55 | Oklahoma State Univ | 0 | 75.2 | 40.7 | 80 | 76.5 | 33.3 | 90.4 | 173.0 | 86.8 | 656.0 |
| 11 | 12 | 65 | Univ of Nebraska - Lincoln | 0 | 77.2 | 40.4 | 100 | 50.2 | 44.0 | 100.6 | 189.3 | 46.8 | 648.6 |
| 12 | 13 | 106 | Univ of Waterloo | 0 | 77.4 | 72.7 | 100 | 60.9 | 23.0 | 99.9 | 134.3 | 73.0 | 641.1 |
| 13 | 14 | 83 | Hope College | 0 | 71.0 | 46.4 | 60 | 61.9 | 48.0 | 79.3 | 187.8 | 65.2 | 619.7 |
| 14 | 15 | 146 | Technische Universitat Berlin | 0 | 79.5 | 71.5 | 148 | 36.2 | 75.0 | 123.5 | 7.0 | 76.9 | 617.6 |
| 15 | 16 | 95 | Saginaw Valley State Univ | 0 | 52.0 | 50.6 | 70 | 68.9 | 45.9 | 103.2 | 173.7 | 46.5 | 610.8 |
| 16 | 17 | 63 | Univ of Kansas - Lawrence | 0 | 40.3 | 67.0 | 80 | 55.9 | 8.0 | 95.4 | 187.5 | 43.2 | 577.3 |
| 17 | 18 | 150 | Univ of North Florida | 0 | 61.1 | 42.9 | 80 | 37.8 | 54.8 | 87.8 | 155.1 | 49.7 | 569.1 |
df = df[df['Cost Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Cost Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Cost', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[61.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Presentation Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Presentation Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Presentation', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[42.9], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Design Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Design Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Design', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[80.0], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Acceleration Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Acceleration Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Acceleration', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[37.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Skid Pad Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Skid Pad Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Skid Pad', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[54.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Autocross Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Autocross Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Autocross', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[87.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores.csv')
df = df[df['Endurance Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Endurance Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Endurance', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[155.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
df = pd.read_csv('scores finished endurance.csv')
df = df[df['Endurance Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Endurance Score', color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Endurance', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[155.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()